STAT151 Lecture 8: 08_Chapter16.pdf

• School: University of Alberta
• Department: Statistics
• Course: STAT151
• Professor: Alireza Simchi

Document Summary

A random variable assumes a value based on the outcome of a random event. We use a capital letter, like x, to denote a random variable. A particular value of a random variable will be denoted with a lower case letter, in this case x. Discrete random variables can take one of a finite number of distinct outcomes. Continuous random variables can take any numeric value within a range of values. X = # of heads - random variable. Probabilities of x: p(x=2) = p({hh}) = . P(x=1) = p({ht, th}) = 2/4 = . Note: any probability of x: 0 p(x) 1, p(x) = 1 x. A probability model for a random variable consists of: The collection of all possible values of a random variable, and. Of particular interest is the value we expect a random variable to take on, notated (for population mean) or e(x) for expected value.